Create sts-sohu2021.py

sts-sohu2021.py

@@ -0,0 +1,102 @@
+# -*- coding: utf-8 -*-
+"""
+@author:XuMing([email protected])
+@description:
+2021搜狐校园文本匹配算法大赛数据集
+upload： https://github.com/shibing624
+"""
+
+
+import csv
+import os
+import json
+import datasets
+
+
+_CITATION = """https://github.com/shibing624/text2vec"""
+
+_DESCRIPTION = """\
+2021搜狐校园文本匹配算法大赛数据集
+"""
+
+_DATA_URL = "https://huggingface.co/datasets/shibing624/sts-sohu2021/resolve/main/"
+
+
+class Sohu(datasets.GeneratorBasedBuilder):
+    """The Chinese Natural Language Inference (sts-sohu) Corpus."""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="dda",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of sts-sohu2021",
+        ),
+        datasets.BuilderConfig(
+            name="ddb",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of sts-sohu2021",
+        ),
+        datasets.BuilderConfig(
+            name="dca",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of sts-sohu2021",
+        ),
+        datasets.BuilderConfig(
+            name="dcb",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of sts-sohu2021",
+        ),
+        datasets.BuilderConfig(
+            name="cca",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of sts-sohu2021",
+        ),
+        datasets.BuilderConfig(
+            name="ccb",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of sts-sohu2021",
+        ),
+        
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "sentence1": datasets.Value("string"),
+                    "sentence2": datasets.Value("string"),
+                    "label": datasets.Value("int32"),
+                }
+            ),
+
+            supervised_keys=None,
+            homepage="https://github.com/shibing624/text2vec",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_DATA_URL)
+        dl_file = f"{dl_dir}/{self.config.name}.jsonl"
+        return [
+            
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": dl_file}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        id = 0
+        if isinstance(filepath, str):
+            filepath = [filepath]
+        for file in filepath:
+            with open(file, encoding="utf-8") as f:
+                for key, row in enumerate(f):
+                    data = json.loads(row)
+                    yield id, {
+                            "sentence1": data["sentence1"],
+                            "sentence2": data["sentence2"],
+                            "label": int(data["label"])
+                    }
+                    id += 1